Boughey, Judy C.

529 Background: Neoadjuvant chemotherapy (NAC) is commonly administered to patients (pts) with estrogen receptor alpha (ER) negative (immunohistochemistry [IHC] 0%) and ER-low (IHC 1-10%) breast cancer (BC). For pts without pathological complete response (pCR), ER expression may differ between baseline and residual BC following NAC. We previously demonstrated adjuvant endocrine therapy (ET) omission in ER-low early-stage BC was associated with significantly worse overall survival (OS); however, this effect was restricted to pts with residual BC following NAC and those with higher baseline ER levels (IHC 6-10%) (Choong et al., ASCO 2024). Here, we assessed how often ER was expressed in residual invasive BC for pts treated with NAC for ER-negative and ER-low BC. Methods: Weidentified pts with pre-treatment (tx) ER-negative and ER-low (regardless of HER2 expression) stage I-III BC treated with NAC who underwent BC surgery at Mayo Clinic Rochester between 2009 and 2023. ER IHC was performed in a CAP/CLIA laboratory. We evaluated ER expression in residual invasive BC for pts without pCR. The percent of pts with a post-tx change in ER status was estimated and reported with 95% Wilson confidence intervals. Results: 955 pts (838 [88%] pre-tx ER-negative; 117 [12%] pre-tx ER-low) met inclusion criteria, of whom 69% had HER2-negative and 31% HER2-positive BC. The median age at diagnosis was 52 (range: 24-86). 496 (52%) had residual BC. Residual BC was more common in HER2-negative versus (vs) positive tumors (56% vs 42%, p < 0.001) but did not differ significantly by ER status (ER-negative 51% vs ER-low 57%, p = 0.22). Of those with residual BC, 277/496 (56%) had ER re-testing. Rates of ER re-testing did not vary for pre-tx ER-negative vs -low (57% vs 51%, p = 0.37) but were significantly lower for HER2-positive vs HER2-negative tumors (39% vs 62%, p < 0.001). Among those with post-tx testing, 31/277 (11%, 95% CI: 8-15%) had an increase in ER expression from pretreatment levels (defined as ER IHC < 1% to either 1-10% or > 10%; or ER IHC 1-10% to > 10%). In these 31 pts, the original NAC was for either TNBC (21/31; 68%) or HER2+ BC (10/31; 32%). In pts with pre-tx ER-negative BC, 27/243 (11%, 95% CI: 8-16%) had ER expression in the residual BC including 14/243 (6%, 95% CI: 3-9%) with ER > 10% and 13/243 (5%, 95% CI: 3-9%) with ER 1-10%. For pts with baseline ER-low BC, 4/34 (12%, 95% CI: 5-27%) had ER > 10% in the residual BC. Among the 31 pts where ER increased following NAC, 21/31 (68%) received adjuvant ET, including 17/18 if ER was > 10% in the residual disease and 4/13 in those with ER 1-10%. Conclusions: In pts treated with NAC for ER-negative or ER-low BC not achieving pCR, we identified higher ER expression in the residual breast cancer in > 10% of pts. Given that omission of ET in ER-low BC with residual cancer following NAC is associated with worse survival, repeat biomarker testing should be considered in those without pCR, and ET individualized according to ER expression.

569 Background: Several studies established the prognostic role of both the amount and locations of tumor-infiltrating lymphocytes (TILs) in TNBC. Three distinct immunotypes were described based on the amount and locations of TILs: immune enriched (IN), immune excluded, and immune desert. Using single-cell spatial transcriptomic analysis in the Mayo Clinic TNBC cohort, our previous studies showed the central role of interferon (IFN) signaling in IN phenotype. Herein, we evaluated the association between IFN and outcomes in TNBC in 3 independent datasets. Methods: NanoString IO360 was performed in 114 samples from FinXX (NCT00114816) to generate 22-gene IFNα and 33-gene IFNγ signatures. RNA sequencing was performed in 388 samples from CALGB 40603 (NCT00861705). 3038 TNBC samples were tested by WTS (NovaSeq; Caris Life Sciences, Phoenix, AZ). Median values were used as cut-offs for high vs low IFNγ RNA expression and 18-gene IFNγ signature scores. Caris Life Science CODEai was used to evaluate real-world overall survival (OS) obtained from insurance claims and calculated from tissue collection to last contact using Kaplan-Meier estimates. Chi-square, Mann-Whitney U, ANOVA, and Cox regression were used. Results: A high 22-gene IFNα signature score was associated with significantly improved recurrence-free survival (RFS) in FinXX (hazard ratio [HR] 0.32, 95% confidence interval [CI] 0.14-0.74, p 0.007) and OS (HR 0.28, 95%CI 0.12-0.66, p 0.003). Similar findings were observed with 33-gene IFNγ signature with significant improvement in RFS (HR 0.21, 95%CI 0.09-0.51, p < 0.001) and OS (HR 0.18, 95%CI 0.08-0.44, p < 0.001). Furthermore, in CALGB 40603, both IFNα and IFNγ scores were positively associated with pathologic complete response (pCR: IFNα p 0.019 and IFNγ p 0.007) and residual cancer burden (RCB: IFNα p 0.044 and IFNγ p 0.013). Using the Caris data platform to further validate, we identified 2899 TNBC patients (pts) with genomic and clinical outcome data. High IFNγ expression was associated with significant improvement in OS (25.95 vs 17.43 months; HR 0.65, 95% CI 0.59 – 0.72, p < 0.001). Similarly, pts with high IFNγ signature scores had significant improvement in median OS (25.79 vs 16.22 months; HR 0.66, 95% CI 0.6 – 0.73, p < 0.001). Conclusions: This study underscores the pivotal role of IFN signaling in TNBC. High IFNα and IFNγ signatures were consistently associated with improved RFS, OS, higher pCR rates, and lower RCB across clinical trial cohorts and real-world data. These findings signify IFN signaling as a potential key biomarker and therapeutic target in TNBC. Support: U10CA180821, U10CA180882, U24CA196171; Breast Cancer Research Foundation, Mayo Clinic Breast Cancer SPORE (P50CA116201-17), Bankhead Coley, W81XWH-15-1-0292, P50CA015083, R35CA253187; https://acknowledgments.alliancefound.org . Genentech. Clinical trial information: NCT00114816 and NCT00861705 .

548 Background: TNBC is associated with higher risk of recurrence and poorer survival rates than other breast cancer subtypes. For node-positive TNBC or tumors larger than 0.5 cm, chemotherapy is generally recommended. For stage I TNBC, the benefit from chemotherapy, the optimal regimen, and whether to administer it in the neoadjuvant versus adjuvant setting remain controversial. Here, we report the treatment patterns and clinical outcomes of patients with stage I TNBC treated at Mayo Clinic. Methods: Using the Mayo Clinic Tumor Registry data, we identified patients with stage I TNBC treated between 2010 and 2021. We used the pathologic tumor (T) category for patients treated with upfront surgery and the clinical T category for patients receiving neoadjuvant chemotherapy. We used the Kaplan-Meier method and log-rank test to compare recurrence-free survival (RFS) according to treatment groups, measured from the day of surgery. RFS was reported at a median follow-up of 3.9, 6.2, and 7.3 years for patients who received chemotherapy neoadjuvantly, adjuvantly, and surgery alone with no chemotherapy, respectively. Results: A total of 602 patients with Stage I TNBC were included, with a median age of 62 years. 290 (48%) underwent upfront surgery followed by adjuvant chemotherapy (pT1a: 2%, pT1b: 25%, pT1c: 74%), 127 (21%) received neoadjuvant chemotherapy followed by surgery (cT1a: 2%, cT1b: 11%, cT1c: 87%), and 185 (31%) underwent primary surgery without any chemotherapy (pT1mi/T1a: 33%, pT1b: 32%, pT1c: 35%). Most patients treated with neoadjuvant therapy received anthracycline/cyclophosphamide + taxane (70%), while most patients treated in the adjuvant setting received a non-anthracycline containing regimen (60%). The 5-year RFS was 96% (95% CI: 93-100%) for patients who received chemotherapy neoadjuvantly, 95% (95% CI: 92-98%) for those who received chemotherapy adjuvantly, and 85% (95% CI: 80-91%) for those treated with surgery alone and no chemotherapy ( P < 0.0001). 71 (56%) of the 127 patients who received neoadjuvant therapy achieved a pCR, with only 1 RFS event (at 14 months) in that group, compared to 4 RFS events among those not achieving pCR (at 12, 20, 28 and 75 months, respectively). Among patients not receiving chemotherapy (either adjuvantly or neoadjuvantly), the 5-year RFS rates were 94% for pT1mi/T1a, 92% for pT1b and 72% for pT1c (T1mi/a/b vs T1c, P = 0.009). Conclusions: In this large cohort of stage I TNBC, patients who received chemotherapy (adjuvantly or neoadjuvantly) had better 5-year RFS compared with those treated with locoregional therapy only. Among patients receiving chemotherapy, 5-year RFS was nearly identical regardless of whether chemotherapy was administered before or after surgery. Interestingly, patients undergoing upfront surgery were more likely to receive an anthracycline-sparing chemotherapy regimen.

504 Background: Axillary surgery in breast cancer is used for staging and therapeutic purposes, but axillary lymph node dissection (ALND) confers high risk of complications including lymphedema. Accordingly, trials have focused on right-sizing axillary surgery, with options ranging from complete omission of surgery, sentinel lymph node (SLN) surgery, targeted axillary dissection (TAD), or ALND. Identifying a biomarker to reliably predict nodal burden would facilitate accurate selection of surgical management. We evaluated whether the presence or absence of ctDNA in the blood pre and post NAC is associated with residual nodal burden. Methods: I-SPY2 is a prospective, multicenter NAC trial for patients with clinical stage II-III high-risk breast cancer. Patients are randomized to novel NAC agents, with pathologic complete response being the primary endpoint. As part of the trial, serial ctDNA is assessed with a highly sensitive tumor-informed assay using up to 16 patient-specific tumor mutations (Signatera) at baseline, 3 weeks, 12 weeks, and post-NAC. We determined whether ctDNA positivity or negativity post-NAC, and the change in ctDNA status baseline/post-NAC (-/-, -/+, +/+, +/-) are associated with ypN category (N0, N1, N2). Results: ctDNA status was available post-NAC in 495 patients and change in ctDNA status from baseline was available in 493. At baseline, ctDNA was detected in 160/220 (72.3%) cN0 patients and 227/273 (83.2%) cN+ patients (p=0.006). Post-NAC, ctDNA was detected in 11/220 (5%) cN0 patients and 34/273 (12.5%) cN+ patients (p=0.004). While baseline ctDNA status was not associated with ypN category, there was a significant association between post-NAC ctDNA status and ypN category. For ctDNA + patients post-NAC, 33.3% were ypN0, 31.1% were ypN1, and 35.6% were ypN2 at surgery; in contrast, for ctDNA - patients post-NAC, 67.1% were ypN0, 23.1% were ypN1, and 9.8% were ypN2 (p<0.0001). Dynamic ctDNA changes were also associated with ypN category, with significantly more ypN0 patients among ctDNA -/- or ctDNA +/- cases, and more ypN2 patients in those who did not clear ctDNA (+/+) (p=0.0001, Table). Conclusions: To our knowledge this is the first study to demonstrate a significant relationship between ctDNA and ypN category, which has important surgical implications. CtDNA negativity was associated with low likelihood of ypN2 disease, making these patients excellent candidates for SLN surgery or TAD. Ongoing analyses will incorporate receptor subtype and timing of clearance of ctDNA. CtDNA in breast cancer may help tailor surgical management of the axilla, potentially reducing patient morbidity without compromising prognostic information. ctDNA baseline/post-NAC ypN0 (n=317) ypN1 (n=116) ypN2 (n=60) ctDNA -/- (n=105) 72.4% 19.1% 8.6% ctDNA -/+ (n=1) 0.0% 100.0% 0.0% ctDNA +/+ (n=44) 34.1% 29.6% 36.4% ctDNA +/- (n=343) 65.9% 23.9% 10.2%

10582 Background: Breast cancer is the most common cancer in young women, with an increasing incidence over the past two decades. This study aims to evaluate the characteristics of young-onset breast cancers among patients aged ≤50 and compare tumor characteristics by germline mutation carrier status. Methods: Patients with breast cancer diagnosis ≤50 years old and evaluated across the Mayo Clinic enterprise between 2000 and 2024 were identified through the prospective Mayo Clinic Breast Cancer Study and the institutional tumor registry. Demographics, tumor characteristics, and clinical outcomes were obtained and described using summary statistics. Germline pathogenic or likely pathogenic variant (PV) carrier status for 5 established breast cancer predisposition genes (BRCA1, BRCA2, ATM, CHEK2 and PALB2) was available in a subset of unselected patients who consented to participation in sequencing studies at Mayo Clinic. Clinical characteristics were compared between PV carriers in each gene and non-carriers utilizing Chi-square test. All tests were two-sided and p-value less than 0.05 was considered statistically significant. Results: Among 8,462 patients (8435 women, 27 men) with breast cancer diagnosis at age ≤50 in the study, the median age of diagnosis of breast cancer was 44 years (range 18 – 49). At diagnosis, 84% had invasive disease, 43% of the tumors were high-grade, 15.8% had triple-negative breast cancer (TNBC), more than two-thirds (67.5%) presented with stage I or II breast cancer, and 3.7% had bilateral breast cancer. Among the 2,527 patients who consented to germline sequencing, 10.1% were found to be carriers of PVs; these included BRCA1 (3.3%), BRCA2 (2.7%), CHEK2 (2.3%), ATM (1.3%), and PALB2 (0.6%). Compared to non-carriers, a significant enrichment (p<0.05) of invasive breast cancer (92.6% vs. 83.3%) and high grade tumors (61.7% vs. 31.4%) were noted in BRCA1 PV carriers, and of bilateral breast cancer (13.4% vs. 3.8%) and high grade tumors (46.4% vs. 31.4%) in BRCA2 PV carriers. After exclusion of in-situ disease, proportion of TNBC was observed to be significantly higher in BRCA1 (61.3%), BRCA2 (15.5%) and PALB2 (30.7%) PV carriers compared to non-carriers (11.2%), whereas >90% of ATM or CHEK2 PV carriers had ER+ breast cancer and none had TNBC. A significant difference in stage at presentation was not observed by germline PV carrier status. Conclusions: The high frequency (>10%) of PVs in young-onset breast cancer underscores the importance for genetic testing in this population. The observed differences in breast cancer phenotypes based on germline PV carrier status among young-women may have significant implications for clinical outcomes and needs to be further explored.

Abstract Background: Endocrine therapy (ET) with aromatase inhibitors (AI) plus ovarian function suppression (OFS) is standard for premenopausal women with ER+/HER2- breast cancer. However, many premenopausal women are intolerant of AI + OFS, leaving tamoxifen (with or without OFS) as their only option. Extensive studies have demonstrated that premenopausal women treated with neoadjuvant ET whose tumors exhibit Ki-67 ≤ 10% following 4 weeks of therapy (defined as endocrine sensitive disease (ESD)) achieve 5-year distant disease-free survival &gt; 96%. Problematically, only 41% of patients reach this ESD threshold with tamoxifen compared to 78% with AI+OFS (Nitz JCO 2022). (Z)-endoxifen (ENDX) is a potent selective estrogen receptor modulator (SERM) that inhibits ERα at plasma concentrations of 3-5 ng/ml and dually targets PKCβ1, a suspected oncogene in breast tumors, at concentrations ≥ 500 ng/ml. We therefore developed the EVANGELINE study (NCT05607004) is an open label, randomized neoadjuvant phase II study that includes a pharmacokinetic (PK) Run-in, aiming to evaluate whether ENDX +/- goserelin is non-inferior to exemestane plus goserelin with respect to ESD rate. Following the completed PK run-in portion of the study, where 40mg/day or 80mg/day ENDX were assessed, the 40 mg/day dose was selected for further evaluation in the second part of the trial. The second part is comprised of a randomized treatment cohort, for patients with a Ki-67% &gt;10% at preregistration randomized to either 40mg (Z)-endoxifen + goserelin or exemestane + goserelin neoadjuvant treatment and a Single Arm Treatment Cohort for patients who have a Ki-67 ≤ 10% at pre-registration assigned to 40mg/day (Z)-endoxifen monotherapy neoadjuvant treatment. Methods: To investigate ENDX further in premenopausal women, a multicenter study in the United States, was designed(EVANGELINE; NCT05607004). This phase 2, open-label, randomized, neoadjuvant trial includes a PK run-in phase designed to assess whether the 4-week ESD rate with (Z)-endoxifen + goserelin is non-inferior to that of exemestane + goserelin in premenopausal women with Stage IIA or IIB ER+/HER2- breast cancer with diagnostic Ki67 &gt; 10%. Additionally, a single arm Phase 2, open-label neoadjuvant Cohort was designed to assess the 4-week ESD rate with ENDX monotherapy in premenopausal women with Stage IIA or IIB ER+/HER2- BC with diagnostic Ki67 ≤10%. Subjects will undergo neoadjuvant treatment for six months before receiving surgical treatment in the involved breast. This study will additionally assess safety, tolerability, response rates, surgical outcomes, and monitor disease progression. Comprehensive biomarker evaluations will be conducted using paired tumor biopsies and blood samples collected at baseline and week four, as well as 6 month surgical specimens. Enrollment in the PK run-in phase (n-22) was completed in Fall 2024 with the second portion of the trial slated to begin early in 2025. Citation Format: Matthew P. Goetz, Vera J. Suman, Claudia Lopez, Hayley Erickson, Lonnissa Nguyen, Sandra S. Hammer, Lida Mina, Pooja Advani, Roberto Leon-Ferre, Karthik Giridhar, Felipe Batalini, Daniel Flora, Jason M. Jones, Nusayba A. Bagegni, Katie N. Hunt, Mara Piltin, Amy Degnim, James N. Ingle, Judy C. Boughey, Sarah A. Buhrow, Joel M. Reid, Matthew Schellenberg, John R. Hawse, Steven C. Quay. A randomized phase 2 non-inferiority trial of (Z)-endoxifen + goserelin and exemestane + goserelin as neoadjuvant treatment for premenopausal women with ER+/HER2- breast cancer (EVANGELINE) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_2):Abstract nr CT237.

Abstract Purpose: While an addition of immune checkpoint inhibitor (ICI), pembrolizumab, has improved outcomes of patients with TNBC, early-stage TNBC patients with residual cancer burden (RCB) II/III after neoadjuvant chemotherapy in combination with pembrolizumab (NAP) still have poor outcomes. Previously, we demonstrated that intratumoral HLA-DRA expression and interferon-alpha (IFNα) responses were associated with immune-inflamed phenotype and better outcomes in TNBC patients receiving chemotherapy. This study utilized the CosMx™ SMI to investigate in early-stage TNBC treated with NAP. Methods: Of 151 samples from TNBC patients treated with NAP at Mayo Clinic, 8 pre-treatment biopsy samples (5 pCR and 3 RCB II/III were analyzed using the CosMx™ SMI platform. Linear mixed models to assess differential expression (DE), adjusting for hierarchical data structures. DE analyses were expressed as log2-fold changes (logFC), with the Benjamini-Yekutieli method. GSEA and IPA for signaling pathway exploration. Results: 1.7 million cells were identified across 8 samples after stringent quality control. Immune cell profiling revealed higher B cells, plasma cells, plasmablasts, and T cells (CD4 and CD8) in responders, whereas fibroblasts and myeloid cells were enriched in non-responders. DE analysis showed significantly elevated expression of HLA-DRA (logFC 1.955, p&lt;0.001), other MHC class I and II components, and IFNα in responders. Tumor cells in responders exhibited the highest IFNα expression across cell types. GSEA and IPA analysis revealed enrichment in interferon signaling, antigen presentation, and the cGAS-STING pathway, which drives IFNα production. Spatial analysis categorized cells by their proximity to tumor cells: within 50 µm, 50-100 µm, and over 100 µm. T cells, particularly CD8 T cells, showed a distance-dependent distribution, with a higher abundance near tumor cells in responders. CD8 T cell activation scores declined with increasing distance from IFNα-positive tumor cells but remained consistently low near IFNα-negative tumor cells. IFNγ-positive CD8 T cells exhibited higher activation compared to IFNγ-negative cells, with activation levels influenced by proximity to tumor cells. Lastly, MHC expression in tumor cells was examined relative to CD8 T cell proximity. HLA-DRA and CIITA expression decreased as tumor cells were farther from CD8 T cells. Conclusions: This spatially resolved single-cell analysis highlights the pivotal role of tumor-immune interactions in response to pembrolizumab in TNBC. Our data suggest that tumor cells secrete IFNα through the activation of the cGAS-STING pathway, which activates T cells within close proximity, highlighting the potential role of cGAS-STING agonist as well as IFNα signaling and antigen presentation in augmenting TNBC responses to ICIs. Citation Format: Yi Liu, Saranya Chumsri, Yaohua Ma, Jodi M. Carter, Aziza Nassar, Edith Perez, Roberto A. Leon-Ferre, David Zahrieh, David W. Hillman, Judy C. Boughey, James Ingle, Krishna R. Kalari, Fergus J. Couch, Matthew P. Goetz, Keith L. Knutson, E. Aubrey Thompson. Spatially resolved single-cell analysis reveals cGAS-STING-mediated tumor-immune interactions via IFNα as determinants of pembrolizumab sensitivity in triple-negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 7130.

Abstract Deep learning has advanced digital pathology and multi-omics data analysis. However, there is still a critical need to integrate these modalities to better understand complex diseases. Deep learning models, such as Prov-Gigapath, a state-of-the-art pathology foundation model, have been developed for analyzing whole-slide images (WSI). Our previously published deep-learning framework, OmicsFootPrint (OFP), transforms high-dimensional multi-omics data into intuitive genomically-arranged circular images and utilizes transfer learning to overcome the challenges of high-dimensional, low-sample-size data. In this study, we aimed to combine WSI and multi-omics data to develop a framework capable of distinguishing between invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC), which is clinically significant as it may help explain differential responses to therapies, such as tamoxifen versus letrozole. We enhanced the performance of our OFP model by dividing each multi-omics circular image (1024x1024x3 pixels) into 16 equal-sized patches (256x256x3 pixels). Each patch was trained using a separate EfficientNetV2 architecture with pre-trained ImageNet weights. The probability outcomes from these 16 models were subsequently combined through a meta-learner model using the AutoGluon framework. Concurrently, WSI images corresponding to the same patients were independently trained, maintaining consistent train/validation/test splits. The Prov-Gigapath model, which was trained using a dataset from the Providence Health System, was employed to extract patch-level embeddings from the WSI data. These embeddings were fine-tuned using a LongNet-based masked autoencoder to predict outcomes. Finally, predictions from the OFP model and the WSI-based Prov-Gigapath model were integrated through a meta-learner, preserving the original train/validation/test split. Model performances (AUC) were evaluated using the held-out test set. The gold standard used for the analysis was histological identification of IDC versus ILC, against which the performance of omics data alone, WSI data alone, and the multi-modal integration approach were compared. We evaluated our integrated model as a proof-of-concept using The Cancer Genome Atlas (TCGA) breast cancer cohort, comprising 92 ILC and 391 IDC samples. Multi-omics data, including gene expression, microRNA, copy number variation, and RPPA, were analyzed using the OFP framework, while WSI data were processed using the Prov-Gigapath method. The results demonstrated that the multi-modal integration approach significantly outperformed individual modalities, achieving an AUC of 0.98 compared to 0.87 for OFP (original), 0.95 for OFP (16-patches), and 0.92 for WSI. Integrating WSI and multi-omics data improves predictive accuracy, significantly improving the classification of breast cancer subtypes over histology alone. Citation Format: Naresh Prodduturi, Xiaojia Tang, Hamid R. Tizhoosh, Kevin J. Thompson, Richard Weinshilboum, Karthik V. Giridhar, Judy C. Boughey, Eric W. Klee, Liewei Wang, Matthew P. Goetz, Vera Suman, Krishna R. Kalari. A multi-modal learning framework to integrate digital pathology image and multi-omics data in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2429.